
Learning To Use Statistical Tests In Psychology
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Content
- Front cover
- Halftitle
- Title
- Copyright
- Dedication
- Contents
- Preface to the third edition
- Study guide for students
- Acknowledgements
- Part 1 Introduction
- Chapter 1 Research in psychology
- 1.1 Psychological research and statistics
- 1.2 Variability in human behaviour
- 1.3 Relationships between variables
- 1.4 Research hypothesis
- 1.5 Null hypothesis
- 1.6 Rationale for using statistical tests
- 1.7 Participants in psychological research
- Chapter 2 Experiments in psychology
- 2.1 The experimental method
- 2.2 Independent and dependent variables
- 2.3 Experimental and control conditions
- 2.4 Three or more experimental conditions
- 2.5 Same participants (related designs)
- 2.6 Different participants (unrelated designs)
- Chapter 3 Selecting statistical tests
- 3.1 Basic principles for selecting tests
- 3.2 Experiments
- 3.3 Number of experimental conditions
- 3.4 Related or unrelated designs
- 3.5 Non-parametric or parametric tests
- 3.6 Using the Decision Chart
- Chapter 4 Using statistical tests
- 4.1 Variability in data
- 4.2 Probabilities in statistical tables
- 4.3 Selecting a level of significance
- 4.4 One-tailed and two-tailed hypotheses
- Part 2 Statistical tests for experiments
- Chapter 5 Introduction to non-parametric tests
- 5.1 Ordinal data
- 5.2 Assigning ranks to scores
- 5.3 Assigning tied ranks
- 5.4 Standard headings for presenting statistical tests
- Chapter 6 Wilcoxon test (related)
- 6.1 Scores from same participants
- 6.2 Ranking differences between conditions
- 6.3 Ranking plus and minus differences
- 6.4 Ties between scores
- 6.5 Selecting a statistical test in the Decision Chart
- 6.6 Using the Wilcoxon test (related)
- Chapter 7 Mann-Whitney test (unrelated)
- 7.1 Scores from different participants
- 7.2 Overall ranking of scores
- 7.3 Rank totals for each condition
- 7.4 Selecting a statistical test in the Decision Chart
- 7.5 Using the Mann-Whitney test (unrelated)
- Chapter 8 Introduction to parametric t tests
- 8.1 Comparisons between parametric and non-parametric tests
- 8.2 Numerical calculations for parametric tests
- 8.3 Calculating variances
- 8.4 Ratio of variances
- Chapter 9 t test (related)
- 9.1 Scores from same participants
- 9.2 Squaring differences
- 9.3 Ratio of variances
- 9.4 Selecting a statistical test in the Decision Chart
- 9.5 Using the t test (related)
- Chapter 10 t test (unrelated)
- 10.1 Scores from different participants
- 10.2 Squaring scores
- 10.3 Ratio of variances
- 10.4 Selecting a statistical test in the Decision Chart
- 10.5 Using the t test (related)
- Chapter 11 Friedman test (related)
- 11.1 Scores from same participants for three conditions
- 11.2 Ranking three conditions
- 11.3 Assigning tied ranks
- 11.4 Rank totals
- 11.5 Selecting a statistical test in the Decision Chart
- 11.6 Using the Friedman test (related)
- Chapter 12 Kruskal-Wallis test (unrelated)
- 12.1 Scores from different participants for three (or more) conditions
- 12.2 Overall ranking of scores
- 12.3 Totals of ranks for each condition
- 12.4 Selecting a statistical test in the Decision Chart
- 12.5 Using the Kruskal-Wallis test (unrelated)
- 12.6 Note about names of non-parametric tests
- Part 3 Analysis of variance
- Chapter 13 Introduction to ANOVA
- 13.1 Parametric tests
- 13.2 Analysis of variance
- 13.3 Sources of variance
- 13.4 Degrees of freedom
- 13.5 Requirements for parametric tests
- 13.6 Normal distribution
- 13.7 Computer statistical packages
- Chapter 14 One-way ANOVA (unrelated)
- 14.1 Scores from different participants
- 14.2 Definitions of variance
- 14.3 Selecting a statistical test in the Decision Chart
- 14.4 Using one-way ANOVA (unrelated)
- Chapter 15 One-way ANOVA (related)
- 15.1 Scores from same participant
- 15.2 Definitions of variance
- 15.3 Selecting a statistical test in the Decision Chart
- 15.4 Using one-way ANOVA (related)
- Chapter 16 Comparisons between ANOVA conditions
- 16.1 Overall differences in ANOVA
- 16.2 Graphs showing patterns of mean scores
- 16.3 Comparisons between individual conditions
- 16.4 Multiple comparisons between conditions
- 16.5 Using t tests for pairs of conditions
- 16.6 Adjusting significance levels
- 16.7 Bonferroni test
- 16.8 Tukey's honestly significant difference
- Chapter 17 Introduction to two-way ANOVA
- 17.1 Comparison with one-way ANOVA
- 17.2 Two-way ANOVA
- 17.3 Two-by-two tables
- 17.4 Interpreting interactions
- 17.5 Using graphs to demonstrate interactions
- Chapter 18 Two-way ANOVA (unrelated)
- 18.1 Scores from different participants
- 18.2 Definitions of variances
- 18.3 Selecting a statistical test in the Decision Chart
- 18.4 Using two-way ANOVA (unrelated)
- 18.5 Using graphs
- Chapter 19 Two-way ANOVA (related)
- 19.1 Scores from same participants
- 19.2 Definitions of variances
- 19.3 Selecting a statistical test in the Decision Chart
- 19.4 Using two-way ANOVA (related)
- 19.5 Using the SPSS computer program
- 19.6 Note about mixed designs
- Part 4 Relationships between variables
- Chapter 20 Chi-square
- 20.1 Comparison with experiments
- 20.2 Measuring categories
- 20.3 Nominal data
- 20.4 Predicting categories
- 20.5 Selecting a statistical test in the Decision Chart
- 20.6 Using the chi-square test
- Chapter 21 Pearson product moment correlation
- 21.1 Comparison with experiments
- 21.2 Measuring variables in correlations
- 21.3 Predicting positive correlations
- 21.4 Predicting negative correlations
- 21.5 Correlation coefficients
- 21.6 Selecting a statistical test in the Decision Chart
- 21.7 Using Pearson correlation product moment correlation
- Chapter 22 Introduction to simple linear regression
- 22.1 Comparisons with correlation
- 22.2 Predictor variable and criterion variable
- 22.3 Scatterplots
- 22.4 Regression equation for calculating a regression line
- 22.5 Residual error
- 22.6 Rationale for using ANOVA as a test of linear regression
- 22.7 ANOVA table to test linear regression
- Chapter 23 Multiple regression
- 23.1 Comparisons with simple regression
- 23.2 Objectives of multiple regression
- 23.3 Types of multiple regression
- 23.4 Selecting a statistical test in the Decision Chart
- 23.5 Using multiple regression
- Chapter 24 General linear model
- 24.1 Introduction
- 24.2 The role of error in GLM
- 24.3 Application of the GLM to linear regression
- 24.4 Application of GLM to ANOVA
- 24.5 Conclusions
- Answers to Questions
- Recommended Reading
- References
- Statistical Tables
- Decision Chart
- Back cover
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